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• W3202608727 abstract "String metrics play an important role in various computational tasks. In this paper, we focus on a property shared by a subset of string rearrangement metrics, called pseudo-locality. This subset includes, for example, the swap, interchange and parallel-interchange distances. Intuitively, operators of pseudo-local string metrics have a bounded effect on the Hamming distance between the string prior to the operation and after it. The goal of this paper is to examine how to exploit pseudo-locality in order to transform tools derived for the Hamming distance in order to derive tools for other pseudo-local metrics. Specifically, we demonstrate such a way to exploit pseudo-locality of the interchange distance combined with additional techniques to derive: 1.The first efficient approximate nearest-neighbour (ANN) search data structure for the interchange distance, which is (mathcal {NP})-hard to compute for general strings even for binary alphabets.2.The first linear time algorithm to compute approximate pattern matching with interchanges, which is a vast improvement from the (varTheta (nm)) known algorithm." @default.
• W3202608727 created "2021-10-11" @default.
• W3202608727 creator A5007410355 @default.
• W3202608727 date "2021-01-01" @default.
• W3202608727 modified "2023-10-14" @default.
• W3202608727 title "Exploiting Pseudo-locality of Interchange Distance" @default.
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• W3202608727 doi "https://doi.org/10.1007/978-3-030-86692-1_19" @default.
• W3202608727 hasPublicationYear "2021" @default.
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